Literature DB >> 22357564

High-content screening data management for drug discovery in a small- to medium-size laboratory: results of a collaborative pilot study focused on user expectations as indicators of effectiveness.

Cynthia A Berlinicke1, Christopher F Ackermann, Steve H Chen, Christoph Schulze, Yakov Shafranovich, Sahiti Myneni, Vimla L Patel, Jian Wang, Donald J Zack, Mikael Lindvall, G Steven Bova.   

Abstract

High-content screening (HCS) technology provides a powerful vantage point to approach biological problems; it allows analysis of cell parameters, including changes in cell or protein movement, shape, or texture. As part of a collaborative pilot research project to improve bioscience research data integration, we identified HCS data management as an area ripe for advancement. A primary goal was to develop an integrated data management and analysis system suitable for small- to medium-size HCS programs that would improve research productivity and increase work satisfaction. A system was developed that uses Labmatrix, a Web-based research data management platform, to integrate and query data derived from a Cellomics STORE database. Focusing on user expectations, several barriers to HCS productivity were identified and reduced or eliminated. The impact of the project on HCS research productivity was tested through a series of 18 lab-requested integrated data queries, 7 of which were fully enabled, 7 partially enabled, and 4 enabled through data export to standalone data analysis tools. The results are limited to one laboratory, but this pilot suggests that through an "implementation research" approach, a network of small- to medium-size laboratories involved in HCS projects could achieve greater productivity and satisfaction in drug discovery research.

Mesh:

Year:  2012        PMID: 22357564     DOI: 10.1177/2211068211431207

Source DB:  PubMed          Journal:  J Lab Autom        ISSN: 2211-0682


  1 in total

1.  Resolving complex research data management issues in biomedical laboratories: Qualitative study of an industry-academia collaboration.

Authors:  Sahiti Myneni; Vimla L Patel; G Steven Bova; Jian Wang; Christopher F Ackerman; Cynthia A Berlinicke; Steve H Chen; Mikael Lindvall; Donald J Zack
Journal:  Comput Methods Programs Biomed       Date:  2015-11-12       Impact factor: 5.428

  1 in total

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